@NoHatCoder Not sure what you mean by "supersampling" in this case?
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Replying to @cmuratori
@cmuratori Lots of samples per output pixel. There is a wealth of different specific methods, all of them should produce better results.1 reply 0 retweets 0 likes -
Replying to @NoHatCoder
@NoHatCoder That doesn't really make any sense? You know exactly all the pixels that are in the original image. You don't need to sample.1 reply 0 retweets 0 likes -
Replying to @cmuratori
@NoHatCoder Any "dense sampling" of the image can still be trivially reduced to a weighted sum of the covered pixels.2 replies 0 retweets 0 likes -
Replying to @cmuratori
@cmuratori Yes, but I'd still call it a sampling pattern. In any case, what actually happens when you choose "bilinear" is that it takes1 reply 0 retweets 0 likes -
Replying to @NoHatCoder
@cmuratori one weighted sample of 4 pixels for every output pixel, leaving most of the original image completely untouched.1 reply 0 retweets 0 likes -
Replying to @NoHatCoder
@NoHatCoder No, nobody does that, not even Photoshop :)2 replies 0 retweets 0 likes -
Replying to @cmuratori
@cmuratori Do you have a better explanation why the result looks like it does?1 reply 0 retweets 0 likes -
Replying to @NoHatCoder
@NoHatCoder Sure. It's standard sampling theory, and the expected result for the filters they have.2 replies 0 retweets 0 likes -
Replying to @cmuratori
@NoHatCoder You can start with Mitchell if you're new to this: http://www.cs.utexas.edu/~fussell/courses/cs384g-fall2013/lectures/mitchell/Mitchell.pdf …1 reply 0 retweets 0 likes
@NoHatCoder I also suspect they don't handle gamma correctly, so their results are even worse than what would already be bad results.
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